This paper looks at a broad array of evidence concerning the recent boom in home prices, and considers what this means for future home prices and the economy. It does not appear possible to explain the boom in terms of fundamentals such as rents or construction costs. A psychological theory,...

This paper looks for markers of ends of real estate booms or busts. The changes in market psychology and related indicators that occurred at real estate market turning points in the United States since the 1980s are compared with changes at turning points in the more distant past. In all these...

It is widely claimed that housing wealth, as well as stock prices, have an impact on consumption and hence on aggregate economic activity. This paper presents a broad overview of the issues that arise in evaluating this claim in the context of recent research in behavioral economics. Particular...

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized regression techniques. We focus on linear models where the slope parameters are heterogeneous across groups but homogenous within a group and the group membership is...

Reduced rank regression procedures in error correction models (ECM's) permit consistent estimation of the cointegration space but do not provide consistent estimates of individual structural relations when the dimension of the cointegration space is greater than one. Indeed, individual...

A new family of kernels is suggested for use in heteroskedasticity and autocorrelation consistent (HAC) and long run variance (LRV) estimation and robust regression testing. The kernels are constructed by taking powers of the Bartlett kernel and are intended to be used with no truncation (or...

Using the power kernels of Phillips, Sun and Jin (2006, 2007), we examine the large sample asymptotic properties of the t-test for different choices of power parameter (rho). We show that the nonstandard fixed-rho limit distributions of the t-statistic provide more accurate approximations to the...

The Kalman filter is sued to derive updating equations for the Bayesian data density in discrete time linear regression models with stochastic regressors. The implied "Bayes model" has time varying parameters and conditionally heterogeneous error variances. A sigma-finite "Bayes model" measure...

This paper studies fractional processes that may be perturbed by weakly dependent time series. The model for a perturbed fractional process has a components framework in which there may be components of both long and short memory. All commonly used estimates of the long memory parameter (such as...

In this paper we introduce a family of minimum distance from independence estimators, suggested by Manski's minimum mean square from independence estimator. We establish strong consistency, asymptotic normality and consistency of resampling estimates of the distribution and variance of these...